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Multiple Sclerosis => MS - RESEARCH AND NEWS => Topic started by: agate on February 05, 2017, 03:57:52 pm

Title: (Abst.) Age-related MS severity score: Disability ranked by age
Post by: agate on February 05, 2017, 03:57:52 pm
This article makes the point that using the date of onset as a measure of presumed MS severity might by less useful than considering the person's age--since the date of onset is so often difficult to determine with accuracy.

From Multiple Sclerosis Journal, February 5, 2017:

Quote
Age Related Multiple Sclerosis Severity Score: Disability ranked by age

Ali Manouchehrinia, Helga Westerlind, Elaine Kingwell, Feng Zhu, Robert Carruthers, Ryan Ramanujam, Maria Ban, Anna Glaser, Stephen Sawcer, Helen Tremlett, Jan Hillert


Background:

The Multiple Sclerosis Severity Score (MSSS) is obtained by normalising the Expanded Disability Status Scale (EDSS) score for disease duration and has been a valuable tool in cross-sectional studies.

Objective:

To assess whether use of age rather than the inherently ambiguous disease duration was a feasible approach.

Method:


We pooled disability data from three population-based cohorts and developed an Age Related Multiple Sclerosis Severity (ARMSS) score by ranking EDSS scores based on the patient’s age at the time of assessment. We established the power to detect a difference between groups afforded by the ARMSS score and assessed its relative consistency over time.

Results:


The study population included 26058 patients from Sweden (n = 11846), Canada (n = 6179) and the United Kingdom (n = 8033). There was a moderate correlation between EDSS and disease duration (r = 0.46, 95% confidence interval (CI): 0.45–0.47) and between EDSS and age (r = 0.44, 95% CI: 0.43–0.45). The ARMSS scores showed comparable power to detect disability differences between groups to the updated and original MSSS.

Conclusion:


Since age is typically unbiased and readily obtained, and the ARMSS and MSSS were comparable, the ARMSS may provide a more versatile tool and could minimise study biases and loss of statistical power caused by inaccurate or missing onset dates.